Abstract
BackgroundClinical decision support (CDS) is a tool that helps clinicians in decision making by generating clinical alerts to supplement their previous knowledge and experience. However, CDS generates a high volume of irrelevant alerts, resulting in alert fatigue among clinicians. Alert fatigue is the mental state of alerts consuming too much time and mental energy, which often results in relevant alerts being overridden unjustifiably, along with clinically irrelevant ones. Consequently, clinicians become less responsive to important alerts, which opens the door to medication errors.ObjectiveThis study aims to explore how a blockchain-based solution can reduce alert fatigue through collaborative alert sharing in the health sector, thus improving overall health care quality for both patients and clinicians.MethodsWe have designed a 4-step approach to answer this research question. First, we identified five potential challenges based on the published literature through a scoping review. Second, a framework is designed to reduce alert fatigue by addressing the identified challenges with different digital components. Third, an evaluation is made by comparing MedAlert with other proposed solutions. Finally, the limitations and future work are also discussed.ResultsOf the 341 academic papers collected, 8 were selected and analyzed. MedAlert securely distributes low-level (nonlife-threatening) clinical alerts to patients, enabling a collaborative clinical decision. Among the solutions in our framework, Hyperledger (private permissioned blockchain) and BankID (federated digital identity management) have been selected to overcome challenges such as data integrity, user identity, and privacy issues.ConclusionsMedAlert can reduce alert fatigue by attracting the attention of patients and clinicians, instead of solely reducing the total number of alerts. MedAlert offers other advantages, such as ensuring a higher degree of patient privacy and faster transaction times compared with other frameworks. This framework may not be suitable for elderly patients who are not technology savvy or in-patients. Future work in validating this framework based on real health care scenarios is needed to provide the performance evaluations of MedAlert and thus gain support for the better development of this idea.
Highlights
Clinical decision support (CDS) is a tool to facilitate medical decision making by generating clinical alerts [1], ranging from simple medication-specific alerts based on stored clinical rules and information to more complex patient-specific alerts by integrating CDS with electronic health records (EHRs) [2]
Carli et al [35], Powers et al [36], and Hussain et al [37] pointed out that the high degree of alerts with low clinical relevance is one of the root causes of alert fatigue in their systematic literature reviews. This is because hospitals and other private health care institutions use or purchase commercial CDS tools to improve the overall quality of their health care systems
It is common for vendors and designers of commercial CDS tools to sharply restrict the ability to modify the setup for alert systems, resulting in a high volume of low-relevance alerts [2]
Summary
BackgroundClinical decision support (CDS) is a tool to facilitate medical decision making by generating clinical alerts [1], ranging from simple medication-specific alerts based on stored clinical rules and information to more complex patient-specific alerts by integrating CDS with electronic health records (EHRs) [2]. CDS warns clinicians by generating an alert if a new prescription poses a threat to patients [3]. This real-time alert disrupts the workflow and draws clinicians’ attention so they can evaluate and make appropriate decisions in a quick and efficient manner [4]. CDS generates a high volume of irrelevant alerts, resulting in alert fatigue among clinicians. Objective: This study aims to explore how a blockchain-based solution can reduce alert fatigue through collaborative alert sharing in the health sector, improving overall health care quality for both patients and clinicians. MedAlert offers other advantages, such as ensuring a higher degree of patient privacy and faster transaction times compared with other frameworks. Future work in validating this framework based on real health care scenarios is needed to provide the performance evaluations of MedAlert and gain support for the better development of this idea
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